Open source tools for the information theoretic analysis of neural data

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Open source tools for the information theoretic analysis of neural data. / Ince, Robin A A; Mazzoni, Alberto; Petersen, Rasmus S; Panzeri, Stefano.

in: FRONT NEUROSCI-SWITZ, Jahrgang 4, 15.05.2010.

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@article{c836e62f829a481ca456b1bd159c2684,
title = "Open source tools for the information theoretic analysis of neural data",
abstract = "The recent and rapid development of open source software tools for the analysis of neurophysiological datasets consisting of simultaneous multiple recordings of spikes, field potentials and other neural signals holds the promise for a significant advance in the standardization, transparency, quality, reproducibility and variety of techniques used to analyze neurophysiological data and for the integration of information obtained at different spatial and temporal scales. In this review we focus on recent advances in open source toolboxes for the information theoretic analysis of neural responses. We also present examples of their use to investigate the role of spike timing precision, correlations across neurons, and field potential fluctuations in the encoding of sensory information. These information toolboxes, available both in MATLAB and Python programming environments, hold the potential to enlarge the domain of application of information theory to neuroscience and to lead to new discoveries about how neurons encode and transmit information.",
author = "Ince, {Robin A A} and Alberto Mazzoni and Petersen, {Rasmus S} and Stefano Panzeri",
year = "2010",
month = may,
day = "15",
doi = "10.3389/neuro.01.011.2010",
language = "English",
volume = "4",
journal = "FRONT NEUROSCI-SWITZ",
issn = "1662-453X",
publisher = "Frontiers Media S. A.",

}

RIS

TY - JOUR

T1 - Open source tools for the information theoretic analysis of neural data

AU - Ince, Robin A A

AU - Mazzoni, Alberto

AU - Petersen, Rasmus S

AU - Panzeri, Stefano

PY - 2010/5/15

Y1 - 2010/5/15

N2 - The recent and rapid development of open source software tools for the analysis of neurophysiological datasets consisting of simultaneous multiple recordings of spikes, field potentials and other neural signals holds the promise for a significant advance in the standardization, transparency, quality, reproducibility and variety of techniques used to analyze neurophysiological data and for the integration of information obtained at different spatial and temporal scales. In this review we focus on recent advances in open source toolboxes for the information theoretic analysis of neural responses. We also present examples of their use to investigate the role of spike timing precision, correlations across neurons, and field potential fluctuations in the encoding of sensory information. These information toolboxes, available both in MATLAB and Python programming environments, hold the potential to enlarge the domain of application of information theory to neuroscience and to lead to new discoveries about how neurons encode and transmit information.

AB - The recent and rapid development of open source software tools for the analysis of neurophysiological datasets consisting of simultaneous multiple recordings of spikes, field potentials and other neural signals holds the promise for a significant advance in the standardization, transparency, quality, reproducibility and variety of techniques used to analyze neurophysiological data and for the integration of information obtained at different spatial and temporal scales. In this review we focus on recent advances in open source toolboxes for the information theoretic analysis of neural responses. We also present examples of their use to investigate the role of spike timing precision, correlations across neurons, and field potential fluctuations in the encoding of sensory information. These information toolboxes, available both in MATLAB and Python programming environments, hold the potential to enlarge the domain of application of information theory to neuroscience and to lead to new discoveries about how neurons encode and transmit information.

U2 - 10.3389/neuro.01.011.2010

DO - 10.3389/neuro.01.011.2010

M3 - SCORING: Journal article

C2 - 20730105

VL - 4

JO - FRONT NEUROSCI-SWITZ

JF - FRONT NEUROSCI-SWITZ

SN - 1662-453X

ER -